Diagnostic - one model
Erica Goto
2/10/2019
Library & Dataset
Using OLR
Inspect Dataset Using Training and Validation
OLR Equations
- Using all variables
Inspect Dataset Using Training and Validation
- Training set divide in the Diagnostic_based.on.Harell.Rmd file
vclust <- varclus (~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil + TC_weath_rock + TC_unstable_structure + T_construction + spring + landfill + garbage + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank + tree + ground_veg + deforestation + banana + drainage , data=train.data)
# took out density since training has 0 d4 and it was not allowing do the plot
p <- plot(vclust)
par(mfrow=c(6,5))
plot.xmean.ordinaly (risk~angle+brick+wood+mixed+ density+EN +TC + TC_mature_soil + TC_saprolite_soil + TC_weath_rock + TC_unstable_structure + T_construction + spring + landfill + garbage + crack + leaning_wall + scars + downward_floor + tilted + fracture + conc_rainfall + wastewater + leak + septic_tank + tree + ground_veg + deforestation + banana + drainage, data=train.data, cr=TRUE , subn=FALSE)
#angle + building+density+EN +TC + TC_mature_Soil + TC_saprolito + TC_weath_rock + TC_rock + TC_geol_desfav + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + DepTaludeAterro + aterro + lixo + entulho + crack + belly_wall + scars + drawback + tilted + fracture + conc_rainfall_water + wastewater + leak + septic_tank + drainage + tree + ground_veg + deforestation + banana Diagnostic 2: Proportion (-5% of one of the parameters based on what is expected. Since some parameters have 2 predictors, others 5)
#library(plyr)
brick <- count(train.data$brick) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "brick")
wood <- count(train.data$wood) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "wood")
mixed <- count(train.data$mixed) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "mixed")
TC_mature_soil <- count(train.data$TC_mature_soil) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_mature_soil")
T_construction <- count(train.data$T_construction ) %>%
mutate ("Percentage"=(freq/265)*100) %>%
mutate("Classifier" = "T_construction ")
spring <- count(train.data$spring) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "spring")
landfill <- count(train.data$landfill) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "landfill")
garbage <- count(train.data$garbage) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "garbage")
crack <- count(train.data$crack) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "crack")
leaning_wall <- count(train.data$leaning_wall) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "leaning_wall")
scars <- count(train.data$scars) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "DepTaludeAterro")
downward_floor <- count(train.data$downward_floor) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "scars")
tilted <- count(train.data$tilted) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "tilted")
conc_rainfall <- count(train.data$conc_rainfall) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "conc_rainfall")
wastewater <- count(train.data$wastewater) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "wastewater")
leak <- count(train.data$leak) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "conc_rainfall_water")
septic_tank <- count(train.data$septic_tank) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "septic_tank")
angle <- count(train.data$angle) # angle A less than 5% but the rest are okay (3,50, 91, 277, 109) Expected=106
angle <- angle %>%
mutate("Percentage"=(freq/106)*100)%>%
mutate("Classifier" = "angle")
EN <- count(train.data$EN) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "EN")
TC <- count(train.data$TC) %>%
mutate ("Percentage"=(freq/265)*100) %>%
mutate("Classifier" = "TC")
TC_saprolite_soil <- count(train.data$TC_saprolite_soil ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_saprolite_soil ")
banana <- count(train.data$banana) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "banana")
drainage <- count(train.data$drainage) %>%
mutate ("Percentage"=(freq/176.7)*100)%>%
mutate("Classifier" = "drainage")
deforestation <- count(train.data$deforestation) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "deforestation")
TC_unstable_structure <- count(train.data$TC_unstable_structure ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_unstable_structure ")
tree <- count(train.data$tree) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "tree")
ground_veg <- count(train.data$ground_veg) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "ground_veg")
density <- count(train.data$density) %>% #(79, 415, 36) # d4 =0
mutate ("Percentage"=(freq/132.5)*100)%>%
mutate("Classifier" = "density")
TC_weath_rock <- count(train.data$TC_weath_rock ) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "TC_weath_rock ")
fracture <- count(train.data$fracture) %>%
mutate ("Percentage"=(freq/265)*100)%>%
mutate("Classifier" = "fracture")
df <- rbind(brick, wood, mixed, TC_mature_soil, T_construction, spring, landfill, garbage, crack, leaning_wall, scars, downward_floor, tilted, conc_rainfall, wastewater, leak, septic_tank, angle, EN, TC, TC_saprolite_soil, banana, drainage, deforestation, TC_unstable_structure, tree, ground_veg,density, TC_weath_rock, fracture)
df## x freq Percentage Classifier
## 1 FALSE 37 13.9622642 brick
## 2 TRUE 493 186.0377358 brick
## 3 FALSE 456 172.0754717 wood
## 4 TRUE 74 27.9245283 wood
## 5 FALSE 489 184.5283019 mixed
## 6 TRUE 41 15.4716981 mixed
## 7 FALSE 252 95.0943396 TC_mature_soil
## 8 TRUE 278 104.9056604 TC_mature_soil
## 9 FALSE 207 78.1132075 T_construction
## 10 TRUE 323 121.8867925 T_construction
## 11 FALSE 509 192.0754717 spring
## 12 TRUE 21 7.9245283 spring
## 13 FALSE 329 124.1509434 landfill
## 14 TRUE 201 75.8490566 landfill
## 15 FALSE 348 131.3207547 garbage
## 16 TRUE 182 68.6792453 garbage
## 17 FALSE 441 166.4150943 crack
## 18 TRUE 89 33.5849057 crack
## 19 FALSE 501 189.0566038 leaning_wall
## 20 TRUE 29 10.9433962 leaning_wall
## 21 FALSE 326 123.0188679 DepTaludeAterro
## 22 TRUE 204 76.9811321 DepTaludeAterro
## 23 FALSE 462 174.3396226 scars
## 24 TRUE 68 25.6603774 scars
## 25 FALSE 428 161.5094340 tilted
## 26 TRUE 102 38.4905660 tilted
## 27 FALSE 18 6.7924528 conc_rainfall
## 28 TRUE 512 193.2075472 conc_rainfall
## 29 FALSE 200 75.4716981 wastewater
## 30 TRUE 330 124.5283019 wastewater
## 31 FALSE 336 126.7924528 conc_rainfall_water
## 32 TRUE 194 73.2075472 conc_rainfall_water
## 33 FALSE 525 198.1132075 septic_tank
## 34 TRUE 5 1.8867925 septic_tank
## 35 C 35 33.0188679 angle
## 36 D 128 120.7547170 angle
## 37 E 367 346.2264151 angle
## 38 FALSE 344 129.8113208 EN
## 39 TRUE 186 70.1886792 EN
## 40 FALSE 28 10.5660377 TC
## 41 TRUE 502 189.4339623 TC
## 42 FALSE 446 168.3018868 TC_saprolite_soil
## 43 TRUE 84 31.6981132 TC_saprolite_soil
## 44 FALSE 355 133.9622642 banana
## 45 TRUE 175 66.0377358 banana
## 46 Y 63 35.6536503 drainage
## 47 P 243 137.5212224 drainage
## 48 N 224 126.7685342 drainage
## 49 FALSE 498 187.9245283 deforestation
## 50 TRUE 32 12.0754717 deforestation
## 51 FALSE 516 194.7169811 TC_unstable_structure
## 52 TRUE 14 5.2830189 TC_unstable_structure
## 53 FALSE 203 76.6037736 tree
## 54 TRUE 327 123.3962264 tree
## 55 FALSE 154 58.1132075 ground_veg
## 56 TRUE 376 141.8867925 ground_veg
## 57 d1 68 51.3207547 density
## 58 d2 425 320.7547170 density
## 59 d3 37 27.9245283 density
## 60 FALSE 519 195.8490566 TC_weath_rock
## 61 TRUE 11 4.1509434 TC_weath_rock
## 62 FALSE 529 199.6226415 fracture
## 63 TRUE 1 0.3773585 fractureTC_weath_rock, TC_rock_TC_geol_desf, fracture, TC_rock
- OF: angle (slope angle), building (building material), EN (natural slope), TC_saprolito (cut slope with saprolite), Taterro (slope with landfill), DepEncostaNatural (natural slope with construction material), DepTaludeAterro (slope with landfill and construction material), DepTaludeCorte (cut slope with construction material), landfill, garbage, construction_deposit (construction material), crack, leaning_wall, scars, downward_floor, tilted, conc_rainfall_water (concentration of rainfall water), wastewater, leak, drainage
- MOF:TC_mature_soil (slope cut with soil), density, TC (slope cut), - - TC_geol_desfav (cut slope with geology favorable to instability), tree, ground_veg (ground vegetation), deforestation, banana
- NOF: TC_weath_rock (cut slope with weathering rock), TC_rock (cut slope in bedrock), fracture, septic_tank
- GP:all classifiers minus BP classifiers
- BP: TC_weath_rock (True N= 11 , False N= 529), TC_geol_desf (True N= 11 , False N= 529), fracture (True N=1 , False N=529), TC_rock (True N=1 , False N=529 ), septic_tank (True N=4 , False N=526 )
Equation 1
- consider all parameter okay from first diagnostic:
f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana , data=train.data, x=TRUE , y=TRUE)
f1 <- lrm(risk ~ building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + tree + ground_veg + banana + septic_tank +TC_mature_Soil , data=train.data, x=TRUE , y=TRUE) print (f1 , latex =TRUE , coefs =5) stargazer(anova(f1), type=“text”, style=“default”)
# Equation 1
eq_OLR_01 <- polr(risk ~ brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_01))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable## Value Std. Error t value p value
## brickTRUE -0.59105325 0.4451122 -1.3278748 9.210973e-02
## woodTRUE 1.00470094 0.3432157 2.9273161 1.709506e-03
## ENTRUE 0.86440575 0.3842449 2.2496217 1.223649e-02
## TC_mature_soilTRUE 0.80236890 0.2272186 3.5312637 2.067896e-04
## T_constructionTRUE 0.30982524 0.3682327 0.8413843 2.000663e-01
## springTRUE -0.55986054 0.5762272 -0.9715968 1.656256e-01
## landfillTRUE 0.11942449 0.3282493 0.3638226 3.579953e-01
## leakTRUE -0.06685435 0.2309844 -0.2894323 3.861253e-01
## garbageTRUE -0.16306467 0.2962141 -0.5504960 2.909896e-01
## crackTRUE 1.88777942 0.3280415 5.7546966 4.339876e-09
## leaning_wallTRUE 1.49165415 0.5362686 2.7815429 2.705059e-03
## scarsTRUE 3.73175588 0.3634237 10.2683346 4.893985e-25
## downward_floorTRUE 1.17538119 0.3549593 3.3113126 4.642971e-04
## tiltedTRUE 1.16533710 0.3124282 3.7299363 9.576410e-05
## septic_tankTRUE 0.41140123 1.0630605 0.3869970 3.493792e-01
## conc_rainfallTRUE 1.52144121 0.5360700 2.8381393 2.268869e-03
## wastewaterTRUE 0.82069178 0.2362695 3.4735402 2.568202e-04
## ground_vegTRUE 0.98836656 0.2596095 3.8071277 7.029507e-05
## angleD 0.92763711 0.4542142 2.0422899 2.056139e-02
## angleE 1.20893068 0.5357119 2.2566806 1.201402e-02
## TC_saprolite_soilTRUE 0.36070811 0.2947684 1.2237000 1.105327e-01
## R1|R2 1.72364940 0.8749261 1.9700514 2.441624e-02
## R2|R3 5.95423773 0.9362011 6.3599989 1.008776e-10
## R3|R4 11.13817103 1.0614334 10.4935182 4.625893e-26stargazer((ctable), type="text", style="default", digits = 2)##
## ======================================================
## Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE -0.59 0.45 -1.33 0.09
## woodTRUE 1.00 0.34 2.93 0.002
## ENTRUE 0.86 0.38 2.25 0.01
## TC_mature_soilTRUE 0.80 0.23 3.53 0.0002
## T_constructionTRUE 0.31 0.37 0.84 0.20
## springTRUE -0.56 0.58 -0.97 0.17
## landfillTRUE 0.12 0.33 0.36 0.36
## leakTRUE -0.07 0.23 -0.29 0.39
## garbageTRUE -0.16 0.30 -0.55 0.29
## crackTRUE 1.89 0.33 5.75 0
## leaning_wallTRUE 1.49 0.54 2.78 0.003
## scarsTRUE 3.73 0.36 10.27 0
## downward_floorTRUE 1.18 0.35 3.31 0.0005
## tiltedTRUE 1.17 0.31 3.73 0.0001
## septic_tankTRUE 0.41 1.06 0.39 0.35
## conc_rainfallTRUE 1.52 0.54 2.84 0.002
## wastewaterTRUE 0.82 0.24 3.47 0.0003
## ground_vegTRUE 0.99 0.26 3.81 0.0001
## angleD 0.93 0.45 2.04 0.02
## angleE 1.21 0.54 2.26 0.01
## TC_saprolite_soilTRUE 0.36 0.29 1.22 0.11
## R1| R2 1.72 0.87 1.97 0.02
## R2| R3 5.95 0.94 6.36 0
## R3| R4 11.14 1.06 10.49 0
## ------------------------------------------------------less p-value = 0.10 (TC_saprolitoTRUE,TaterroTRUE, DepTaludeAterroTRUE,DepTaludeAterroTRUE,landfillTRUE, construction_depositTRUE, leakTRUE)
par(mfrow=c(5,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
,data=train.data, cr=TRUE , subn=FALSE , cex.lab=1.5, cex.axis=2, cex.sub=2, cex.main=2)
Creating function with four level
Equation 1
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN + TC_mature_soil + T_construction + spring+ landfill+ leak+ garbage+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ septic_tank+ conc_rainfall+ wastewater+ ground_veg + angle + TC_saprolite_soil
, fun=sf))
s## as.numeric(risk) N= 529 , 1 Missing
##
## +-----------------+---+---+----+----------+------------+-----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +-----------------+---+---+----+----------+------------+-----------+
## |brick |No | 37|Inf | 2.8622009| 1.287854288|-0.86020127|
## | |Yes|492|Inf | 2.2958961|-0.089490571|-2.03229476|
## +-----------------+---+---+----+----------+------------+-----------+
## |wood |No |455|Inf | 2.2344036|-0.171850257|-2.25982323|
## | |Yes| 74|Inf | 3.1640676| 1.134979933|-0.67294447|
## +-----------------+---+---+----+----------+------------+-----------+
## |EN |No |343|Inf | 1.8402119|-0.518607764|-2.38209716|
## | |Yes|186|Inf | Inf| 1.000631880|-1.32687094|
## +-----------------+---+---+----+----------+------------+-----------+
## |TC_mature_soil |No |252|Inf | 1.8245493|-0.287682072|-2.25129180|
## | |Yes|277|Inf | 3.0948232| 0.254065462|-1.66684882|
## +-----------------+---+---+----+----------+------------+-----------+
## |T_construction |No |207|Inf | 1.5581446|-0.896088025|-2.98061864|
## | |Yes|322|Inf | 3.3418976| 0.547435369|-1.51550609|
## +-----------------+---+---+----+----------+------------+-----------+
## |spring |No |508|Inf | 2.2832504|-0.047252885|-2.04880457|
## | |Yes| 21|Inf | Inf| 1.163150810|-0.09531018|
## +-----------------+---+---+----+----------+------------+-----------+
## |landfill |No |328|Inf | 1.8387844|-0.523855124|-2.53897387|
## | |Yes|201|Inf | 4.6001576| 0.878289614|-1.27205617|
## +-----------------+---+---+----+----------+------------+-----------+
## |leak |No |335|Inf | 1.9425030|-0.331357136|-2.43426292|
## | |Yes|194|Inf | 3.6323091| 0.571786324|-1.31686585|
## +-----------------+---+---+----+----------+------------+-----------+
## |garbage |No |348|Inf | 2.1288750|-0.207639365|-2.22303246|
## | |Yes|181|Inf | 2.8390785| 0.391671786|-1.46407206|
## +-----------------+---+---+----+----------+------------+-----------+
## |crack |No |440|Inf | 2.1477095|-0.358331030|-2.65129738|
## | |Yes| 89|Inf | 4.4773368| 2.627081139|-0.24846136|
## +-----------------+---+---+----+----------+------------+-----------+
## |leaning_wall |No |500|Inf | 2.2657445|-0.112117298|-2.11133491|
## | |Yes| 29|Inf | Inf| 3.332204510|-0.06899287|
## +-----------------+---+---+----+----------+------------+-----------+
## |scars |No |325|Inf | 1.7774735|-1.348266966|-4.38514676|
## | |Yes|204|Inf | Inf| 3.337293580|-0.78275934|
## +-----------------+---+---+----+----------+------------+-----------+
## |downward_floor |No |461|Inf | 2.1757184|-0.292745374|-2.30020130|
## | |Yes| 68|Inf | Inf| 4.204692619|-0.47957308|
## +-----------------+---+---+----+----------+------------+-----------+
## |tilted |No |427|Inf | 2.0900237|-0.442687819|-2.51314986|
## | |Yes|102|Inf | Inf| 2.965273066|-0.60613580|
## +-----------------+---+---+----+----------+------------+-----------+
## |septic_tank |No |524|Inf | 2.3173689|-0.007633625|-1.93721444|
## | |Yes| 5|Inf | Inf| 0.405465108|-0.40546511|
## +-----------------+---+---+----+----------+------------+-----------+
## |conc_rainfall |No | 18|Inf |-0.2231436|-2.833213344| -Inf|
## | |Yes|511|Inf | 2.5502894| 0.058725286|-1.87406206|
## +-----------------+---+---+----+----------+------------+-----------+
## |wastewater |No |200|Inf | 1.6582281|-0.468378934|-2.75153531|
## | |Yes|329|Inf | 3.0413428| 0.275281559|-1.58412010|
## +-----------------+---+---+----+----------+------------+-----------+
## |ground_veg |No |154|Inf | 1.2992830|-1.378197151|-2.77950917|
## | |Yes|375|Inf | 3.2498206| 0.495211396|-1.67820477|
## +-----------------+---+---+----+----------+------------+-----------+
## |angle |C | 35|Inf | Inf|-0.405465108|-3.52636052|
## | |D |128|Inf | 4.1431347| 1.140723774|-1.22782402|
## | |E |366|Inf | 1.9647786|-0.330854244|-2.15542745|
## +-----------------+---+---+----+----------+------------+-----------+
## |TC_saprolite_soil|No |445|Inf | 2.2352520|-0.103462982|-2.02256589|
## | |Yes| 84|Inf | 2.9957323| 0.536304709|-1.44691898|
## +-----------------+---+---+----+----------+------------+-----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.91389034|
## +-----------------+---+---+----+----------+------------+-----------+plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=1, cex.sub=1)
Equation 2
- parameters okay and so/so
- porportion
- excluded TC_geol_desf
f2 <- lrm(risk ~ angle + building + EN + TC_saprolito + Taterro + DepEncNatural + DepTaludeAterro + DepTaludeCorte + landfill + garbage + construction_deposit + crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + leak + drainage + TC_mature_Soil + density + TC + tree +ground_veg + deforestation + banana , data=train.data, x=TRUE , y=TRUE)
stargazer(anova(f2), type="text", style="default")eq_OLR_02 <- polr(risk ~ brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,
data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_02))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable## Value Std. Error t value p value
## brickTRUE -0.576068918 0.5134422 -1.12197431 1.309367e-01
## woodTRUE 0.792675332 0.3622551 2.18816907 1.432864e-02
## ENTRUE 0.681755803 0.3980095 1.71291339 4.336424e-02
## TC_mature_soilTRUE 0.781258113 0.2385243 3.27538130 5.275972e-04
## T_constructionTRUE 0.443038723 0.3772575 1.17436705 1.201240e-01
## landfillTRUE -0.007528393 0.3346901 -0.02249362 4.910271e-01
## leakTRUE -0.204661794 0.2345357 -0.87262537 1.914337e-01
## garbageTRUE -0.204490873 0.3038862 -0.67291929 2.504993e-01
## crackTRUE 1.929647273 0.3327594 5.79892633 3.337042e-09
## leaning_wallTRUE 1.528083306 0.5512235 2.77216668 2.784226e-03
## treeTRUE -0.141179030 0.2475259 -0.57036070 2.842165e-01
## downward_floorTRUE 1.002041679 0.3597204 2.78561232 2.671336e-03
## tiltedTRUE 1.060599502 0.3124311 3.39466665 3.435610e-04
## ground_vegTRUE 0.782113227 0.2795815 2.79744246 2.575447e-03
## scarsTRUE 3.816548792 0.3741981 10.19927222 9.988188e-25
## mixedTRUE -0.202299358 0.5022234 -0.40280751 3.435449e-01
## conc_rainfallTRUE 1.133438458 0.5672784 1.99802854 2.285678e-02
## wastewaterTRUE 0.608783886 0.2438119 2.49694072 6.263495e-03
## angleD 0.739545136 0.4626426 1.59852382 5.496322e-02
## angleE 1.099510663 0.5417356 2.02960768 2.119822e-02
## bananaTRUE 0.545338039 0.2546905 2.14117947 1.612978e-02
## drainage.L 1.079929448 0.2878552 3.75164167 8.784022e-05
## drainage.Q -0.072325121 0.1881897 -0.38432039 3.503705e-01
## TC_saprolite_soilTRUE 0.310772313 0.3040231 1.02219957 1.533432e-01
## TCTRUE -0.801912872 0.5262570 -1.52380467 6.377876e-02
## deforestationTRUE 0.583959860 0.4344756 1.34405673 8.946502e-02
## R1|R2 0.228779981 1.1150517 0.20517433 4.187180e-01
## R2|R3 4.687203262 1.1392545 4.11427224 1.942014e-05
## R3|R4 9.988986057 1.2425872 8.03886104 4.533867e-16stargazer((ctable), type="text", style="default", digits=2)##
## ======================================================
## Value Std. Error t value p value
## ------------------------------------------------------
## brickTRUE -0.58 0.51 -1.12 0.13
## woodTRUE 0.79 0.36 2.19 0.01
## ENTRUE 0.68 0.40 1.71 0.04
## TC_mature_soilTRUE 0.78 0.24 3.28 0.001
## T_constructionTRUE 0.44 0.38 1.17 0.12
## landfillTRUE -0.01 0.33 -0.02 0.49
## leakTRUE -0.20 0.23 -0.87 0.19
## garbageTRUE -0.20 0.30 -0.67 0.25
## crackTRUE 1.93 0.33 5.80 0
## leaning_wallTRUE 1.53 0.55 2.77 0.003
## treeTRUE -0.14 0.25 -0.57 0.28
## downward_floorTRUE 1.00 0.36 2.79 0.003
## tiltedTRUE 1.06 0.31 3.39 0.0003
## ground_vegTRUE 0.78 0.28 2.80 0.003
## scarsTRUE 3.82 0.37 10.20 0
## mixedTRUE -0.20 0.50 -0.40 0.34
## conc_rainfallTRUE 1.13 0.57 2.00 0.02
## wastewaterTRUE 0.61 0.24 2.50 0.01
## angleD 0.74 0.46 1.60 0.05
## angleE 1.10 0.54 2.03 0.02
## bananaTRUE 0.55 0.25 2.14 0.02
## drainage.L 1.08 0.29 3.75 0.0001
## drainage.Q -0.07 0.19 -0.38 0.35
## TC_saprolite_soilTRUE 0.31 0.30 1.02 0.15
## TCTRUE -0.80 0.53 -1.52 0.06
## deforestationTRUE 0.58 0.43 1.34 0.09
## R1| R2 0.23 1.12 0.21 0.42
## R2| R3 4.69 1.14 4.11 0.0000
## R3| R4 9.99 1.24 8.04 0
## ------------------------------------------------------par(mfrow=c(6,4))
plot.xmean.ordinaly (risk~ brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation
,data=train.data, cr=TRUE , subn=FALSE , cex.lab=1.5, cex.axis=4, cex.sub=4, cex.main=4)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ EN+ TC_mature_soil+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ mixed+ conc_rainfall+ wastewater+ angle+ banana+ drainage+ TC_saprolite_soil+ TC+ deforestation,data=train.data
, fun=sf))
s## as.numeric(risk) N= 529 , 1 Missing
##
## +-----------------+---+---+----+----------+------------+-----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +-----------------+---+---+----+----------+------------+-----------+
## |brick |No | 37|Inf | 2.8622009| 1.287854288|-0.86020127|
## | |Yes|492|Inf | 2.2958961|-0.089490571|-2.03229476|
## +-----------------+---+---+----+----------+------------+-----------+
## |wood |No |455|Inf | 2.2344036|-0.171850257|-2.25982323|
## | |Yes| 74|Inf | 3.1640676| 1.134979933|-0.67294447|
## +-----------------+---+---+----+----------+------------+-----------+
## |EN |No |343|Inf | 1.8402119|-0.518607764|-2.38209716|
## | |Yes|186|Inf | Inf| 1.000631880|-1.32687094|
## +-----------------+---+---+----+----------+------------+-----------+
## |TC_mature_soil |No |252|Inf | 1.8245493|-0.287682072|-2.25129180|
## | |Yes|277|Inf | 3.0948232| 0.254065462|-1.66684882|
## +-----------------+---+---+----+----------+------------+-----------+
## |T_construction |No |207|Inf | 1.5581446|-0.896088025|-2.98061864|
## | |Yes|322|Inf | 3.3418976| 0.547435369|-1.51550609|
## +-----------------+---+---+----+----------+------------+-----------+
## |landfill |No |328|Inf | 1.8387844|-0.523855124|-2.53897387|
## | |Yes|201|Inf | 4.6001576| 0.878289614|-1.27205617|
## +-----------------+---+---+----+----------+------------+-----------+
## |leak |No |335|Inf | 1.9425030|-0.331357136|-2.43426292|
## | |Yes|194|Inf | 3.6323091| 0.571786324|-1.31686585|
## +-----------------+---+---+----+----------+------------+-----------+
## |garbage |No |348|Inf | 2.1288750|-0.207639365|-2.22303246|
## | |Yes|181|Inf | 2.8390785| 0.391671786|-1.46407206|
## +-----------------+---+---+----+----------+------------+-----------+
## |crack |No |440|Inf | 2.1477095|-0.358331030|-2.65129738|
## | |Yes| 89|Inf | 4.4773368| 2.627081139|-0.24846136|
## +-----------------+---+---+----+----------+------------+-----------+
## |leaning_wall |No |500|Inf | 2.2657445|-0.112117298|-2.11133491|
## | |Yes| 29|Inf | Inf| 3.332204510|-0.06899287|
## +-----------------+---+---+----+----------+------------+-----------+
## |tree |No |202|Inf | 1.5976035|-0.678332095|-2.00372972|
## | |Yes|327|Inf | 3.1844436| 0.402917336|-1.86125726|
## +-----------------+---+---+----+----------+------------+-----------+
## |downward_floor |No |461|Inf | 2.1757184|-0.292745374|-2.30020130|
## | |Yes| 68|Inf | Inf| 4.204692619|-0.47957308|
## +-----------------+---+---+----+----------+------------+-----------+
## |tilted |No |427|Inf | 2.0900237|-0.442687819|-2.51314986|
## | |Yes|102|Inf | Inf| 2.965273066|-0.60613580|
## +-----------------+---+---+----+----------+------------+-----------+
## |ground_veg |No |154|Inf | 1.2992830|-1.378197151|-2.77950917|
## | |Yes|375|Inf | 3.2498206| 0.495211396|-1.67820477|
## +-----------------+---+---+----+----------+------------+-----------+
## |scars |No |325|Inf | 1.7774735|-1.348266966|-4.38514676|
## | |Yes|204|Inf | Inf| 3.337293580|-0.78275934|
## +-----------------+---+---+----+----------+------------+-----------+
## |mixed |No |488|Inf | 2.2869073|-0.098440073|-2.04307390|
## | |Yes| 41|Inf | 2.9704145| 1.268511325|-0.88238918|
## +-----------------+---+---+----+----------+------------+-----------+
## |conc_rainfall |No | 18|Inf |-0.2231436|-2.833213344| -Inf|
## | |Yes|511|Inf | 2.5502894| 0.058725286|-1.87406206|
## +-----------------+---+---+----+----------+------------+-----------+
## |wastewater |No |200|Inf | 1.6582281|-0.468378934|-2.75153531|
## | |Yes|329|Inf | 3.0413428| 0.275281559|-1.58412010|
## +-----------------+---+---+----+----------+------------+-----------+
## |angle |C | 35|Inf | Inf|-0.405465108|-3.52636052|
## | |D |128|Inf | 4.1431347| 1.140723774|-1.22782402|
## | |E |366|Inf | 1.9647786|-0.330854244|-2.15542745|
## +-----------------+---+---+----+----------+------------+-----------+
## |banana |No |354|Inf | 1.9266788|-0.412532275|-2.14798386|
## | |Yes|175|Inf | 4.4601444| 0.860940637|-1.53582610|
## +-----------------+---+---+----+----------+------------+-----------+
## |drainage |Y | 63|Inf | 0.8397507|-1.927891644| -Inf|
## | |P |242|Inf | 2.3536403|-0.541801552|-2.58288706|
## | |N |224|Inf | 3.4339872| 1.074942545|-1.22146596|
## +-----------------+---+---+----+----------+------------+-----------+
## |TC_saprolite_soil|No |445|Inf | 2.2352520|-0.103462982|-2.02256589|
## | |Yes| 84|Inf | 2.9957323| 0.536304709|-1.44691898|
## +-----------------+---+---+----+----------+------------+-----------+
## |TC |No | 28|Inf | Inf| 1.299282984|-1.29928298|
## | |Yes|501|Inf | 2.2679496|-0.067890336|-1.95736503|
## +-----------------+---+---+----+----------+------------+-----------+
## |deforestation |No |497|Inf | 2.3826278| 0.052325819|-1.89403832|
## | |Yes| 32|Inf | 1.6863990|-0.938269639|-2.26868354|
## +-----------------+---+---+----+----------+------------+-----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.91389034|
## +-----------------+---+---+----+----------+------------+-----------+plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=1, cex.axis=2, cex.sub=1)
Equation 3
- parameters okay and so/so
- porportion
- p-value based equation 2 > 0.5
f3 <- lrm(risk ~ angle +building + EN + DepTaludeAterro+ DepTaludeCorte+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall_water+ wastewater+ tree + TC , data=train.data, x=TRUE , y=TRUE) stargazer(anova(f3), type=“text”, style=“default”)
# x=TRUE, y=TRUE used by resid() below
eq_OLR_03 <- polr(risk ~ wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, data=train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_03))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable## Value Std. Error t value p value
## woodTRUE 0.8472829 0.3365490 2.5175621 5.908507e-03
## TC_mature_soilTRUE 0.6578579 0.2242972 2.9329743 1.678658e-03
## T_constructionTRUE 0.2597627 0.2942704 0.8827347 1.886898e-01
## landfillTRUE 0.1537936 0.2913467 0.5278714 2.987943e-01
## crackTRUE 1.9633741 0.3216934 6.1032473 5.196743e-10
## leaning_wallTRUE 1.5218562 0.5391654 2.8226146 2.381690e-03
## treeTRUE -0.1048324 0.2347933 -0.4464880 3.276224e-01
## downward_floorTRUE 0.9665673 0.3486718 2.7721405 2.784450e-03
## tiltedTRUE 1.0913213 0.3066097 3.5593176 1.859098e-04
## ground_vegTRUE 0.7964582 0.2691167 2.9595276 1.540556e-03
## scarsTRUE 3.7348373 0.3649582 10.2336034 7.010172e-25
## conc_rainfallTRUE 1.1262103 0.5592657 2.0137303 2.201893e-02
## wastewaterTRUE 0.5329160 0.2368840 2.2496923 1.223424e-02
## bananaTRUE 0.4893149 0.2444585 2.0016271 2.266243e-02
## drainage.L 1.0745434 0.2817741 3.8134922 6.850842e-05
## drainage.Q -0.0649265 0.1860581 -0.3489583 3.635603e-01
## R1|R2 0.4026038 0.5439136 0.7401981 2.295899e-01
## R2|R3 4.7219849 0.6060464 7.7914574 3.312032e-15
## R3|R4 9.8884182 0.7605271 13.0020581 5.954725e-39stargazer((ctable), type="text", style="default", digits = 2)##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE 0.85 0.34 2.52 0.01
## TC_mature_soilTRUE 0.66 0.22 2.93 0.002
## T_constructionTRUE 0.26 0.29 0.88 0.19
## landfillTRUE 0.15 0.29 0.53 0.30
## crackTRUE 1.96 0.32 6.10 0
## leaning_wallTRUE 1.52 0.54 2.82 0.002
## treeTRUE -0.10 0.23 -0.45 0.33
## downward_floorTRUE 0.97 0.35 2.77 0.003
## tiltedTRUE 1.09 0.31 3.56 0.0002
## ground_vegTRUE 0.80 0.27 2.96 0.002
## scarsTRUE 3.73 0.36 10.23 0
## conc_rainfallTRUE 1.13 0.56 2.01 0.02
## wastewaterTRUE 0.53 0.24 2.25 0.01
## bananaTRUE 0.49 0.24 2.00 0.02
## drainage.L 1.07 0.28 3.81 0.0001
## drainage.Q -0.06 0.19 -0.35 0.36
## R1| R2 0.40 0.54 0.74 0.23
## R2| R3 4.72 0.61 7.79 0
## R3| R4 9.89 0.76 13.00 0
## ---------------------------------------------------#print (f3 , latex =TRUE , coefs =5)par(mfrow=c(3,5))
plot.xmean.ordinaly (risk ~ wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage,,
data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~wood+ TC_mature_soil+ T_construction+ landfill+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage, fun=sf))
s## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+-----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+-----------+
## |wood |No |455|Inf | 2.2344036|-0.171850257|-2.25982323|
## | |Yes| 74|Inf | 3.1640676| 1.134979933|-0.67294447|
## +--------------+---+---+----+----------+------------+-----------+
## |TC_mature_soil|No |252|Inf | 1.8245493|-0.287682072|-2.25129180|
## | |Yes|277|Inf | 3.0948232| 0.254065462|-1.66684882|
## +--------------+---+---+----+----------+------------+-----------+
## |T_construction|No |207|Inf | 1.5581446|-0.896088025|-2.98061864|
## | |Yes|322|Inf | 3.3418976| 0.547435369|-1.51550609|
## +--------------+---+---+----+----------+------------+-----------+
## |landfill |No |328|Inf | 1.8387844|-0.523855124|-2.53897387|
## | |Yes|201|Inf | 4.6001576| 0.878289614|-1.27205617|
## +--------------+---+---+----+----------+------------+-----------+
## |crack |No |440|Inf | 2.1477095|-0.358331030|-2.65129738|
## | |Yes| 89|Inf | 4.4773368| 2.627081139|-0.24846136|
## +--------------+---+---+----+----------+------------+-----------+
## |leaning_wall |No |500|Inf | 2.2657445|-0.112117298|-2.11133491|
## | |Yes| 29|Inf | Inf| 3.332204510|-0.06899287|
## +--------------+---+---+----+----------+------------+-----------+
## |tree |No |202|Inf | 1.5976035|-0.678332095|-2.00372972|
## | |Yes|327|Inf | 3.1844436| 0.402917336|-1.86125726|
## +--------------+---+---+----+----------+------------+-----------+
## |downward_floor|No |461|Inf | 2.1757184|-0.292745374|-2.30020130|
## | |Yes| 68|Inf | Inf| 4.204692619|-0.47957308|
## +--------------+---+---+----+----------+------------+-----------+
## |tilted |No |427|Inf | 2.0900237|-0.442687819|-2.51314986|
## | |Yes|102|Inf | Inf| 2.965273066|-0.60613580|
## +--------------+---+---+----+----------+------------+-----------+
## |ground_veg |No |154|Inf | 1.2992830|-1.378197151|-2.77950917|
## | |Yes|375|Inf | 3.2498206| 0.495211396|-1.67820477|
## +--------------+---+---+----+----------+------------+-----------+
## |scars |No |325|Inf | 1.7774735|-1.348266966|-4.38514676|
## | |Yes|204|Inf | Inf| 3.337293580|-0.78275934|
## +--------------+---+---+----+----------+------------+-----------+
## |conc_rainfall |No | 18|Inf |-0.2231436|-2.833213344| -Inf|
## | |Yes|511|Inf | 2.5502894| 0.058725286|-1.87406206|
## +--------------+---+---+----+----------+------------+-----------+
## |wastewater |No |200|Inf | 1.6582281|-0.468378934|-2.75153531|
## | |Yes|329|Inf | 3.0413428| 0.275281559|-1.58412010|
## +--------------+---+---+----+----------+------------+-----------+
## |banana |No |354|Inf | 1.9266788|-0.412532275|-2.14798386|
## | |Yes|175|Inf | 4.4601444| 0.860940637|-1.53582610|
## +--------------+---+---+----+----------+------------+-----------+
## |drainage |Y | 63|Inf | 0.8397507|-1.927891644| -Inf|
## | |P |242|Inf | 2.3536403|-0.541801552|-2.58288706|
## | |N |224|Inf | 3.4339872| 1.074942545|-1.22146596|
## +--------------+---+---+----+----------+------------+-----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.91389034|
## +--------------+---+---+----+----------+------------+-----------+plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.6, cex.axis=0.6, cex.sub=0.6)
Equation 4
- p-value equation 3 > 0.05 (banana, DepTaludeCorte)
- consider proportion
- paremeters okay & so/so
- fashion order
f4 <- lrm(risk ~ building + EN
+ DepEncNatural
+ crack + leaning_wall + scars + downward_floor +tilted + conc_rainfall_water + wastewater + drainage + TC_mature_Soil + TC + +ground_veg
,data=train.data, x=TRUE , y=TRUE) # x=TRUE, y=TRUE used by resid() below #print (f4 , latex =TRUE , coefs =5) stargazer(anova(f4), type=“text”, style=“default”)
eq_OLR_04 <- polr(risk~ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
, data= train.data
, method = "logistic", Hess = TRUE)
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- coef(summary(eq_OLR_04))
ctable <- cbind(ctable, "p value" = p )## Warning in cbind(ctable, `p value` = p): number of rows of result is not a
## multiple of vector length (arg 2)ctable## Value Std. Error t value p value
## woodTRUE 0.85304243 0.3357342 2.5408268 5.908507e-03
## TC_mature_soilTRUE 0.63834225 0.2210786 2.8873996 1.678658e-03
## T_constructionTRUE 0.35590400 0.2312035 1.5393536 1.886898e-01
## crackTRUE 1.97452137 0.3213274 6.1448887 2.987943e-01
## leaning_wallTRUE 1.50670640 0.5398380 2.7910346 5.196743e-10
## treeTRUE -0.11199255 0.2342792 -0.4780303 2.381690e-03
## downward_floorTRUE 0.98265686 0.3472089 2.8301607 3.276224e-01
## tiltedTRUE 1.10777320 0.3049287 3.6328921 2.784450e-03
## ground_vegTRUE 0.80317466 0.2686610 2.9895465 1.859098e-04
## scarsTRUE 3.73867640 0.3650028 10.2428694 1.540556e-03
## conc_rainfallTRUE 1.13903798 0.5591381 2.0371319 7.010172e-25
## wastewaterTRUE 0.50715668 0.2317873 2.1880264 2.201893e-02
## bananaTRUE 0.49314073 0.2442986 2.0185985 1.223424e-02
## drainage.L 1.08506604 0.2810601 3.8606187 2.266243e-02
## drainage.Q -0.05871528 0.1856649 -0.3162433 6.850842e-05
## R1|R2 0.39969336 0.5443680 0.7342338 3.635603e-01
## R2|R3 4.72034503 0.6066484 7.7810224 2.295899e-01
## R3|R4 9.88194863 0.7606510 12.9914364 3.312032e-15stargazer((ctable), type="text", style="default", digits=2)##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## woodTRUE 0.85 0.34 2.54 0.01
## TC_mature_soilTRUE 0.64 0.22 2.89 0.002
## T_constructionTRUE 0.36 0.23 1.54 0.19
## crackTRUE 1.97 0.32 6.14 0.30
## leaning_wallTRUE 1.51 0.54 2.79 0
## treeTRUE -0.11 0.23 -0.48 0.002
## downward_floorTRUE 0.98 0.35 2.83 0.33
## tiltedTRUE 1.11 0.30 3.63 0.003
## ground_vegTRUE 0.80 0.27 2.99 0.0002
## scarsTRUE 3.74 0.37 10.24 0.002
## conc_rainfallTRUE 1.14 0.56 2.04 0
## wastewaterTRUE 0.51 0.23 2.19 0.02
## bananaTRUE 0.49 0.24 2.02 0.01
## drainage.L 1.09 0.28 3.86 0.02
## drainage.Q -0.06 0.19 -0.32 0.0001
## R1| R2 0.40 0.54 0.73 0.36
## R2| R3 4.72 0.61 7.78 0.23
## R3| R4 9.88 0.76 12.99 0
## ---------------------------------------------------par(mfrow=c(4,4))
plot.xmean.ordinaly (risk ~ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ tree+ downward_floor+ tilted+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana+ drainage
, fun=sf))
s## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+-----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+-----------+
## |wood |No |455|Inf | 2.2344036|-0.171850257|-2.25982323|
## | |Yes| 74|Inf | 3.1640676| 1.134979933|-0.67294447|
## +--------------+---+---+----+----------+------------+-----------+
## |TC_mature_soil|No |252|Inf | 1.8245493|-0.287682072|-2.25129180|
## | |Yes|277|Inf | 3.0948232| 0.254065462|-1.66684882|
## +--------------+---+---+----+----------+------------+-----------+
## |T_construction|No |207|Inf | 1.5581446|-0.896088025|-2.98061864|
## | |Yes|322|Inf | 3.3418976| 0.547435369|-1.51550609|
## +--------------+---+---+----+----------+------------+-----------+
## |crack |No |440|Inf | 2.1477095|-0.358331030|-2.65129738|
## | |Yes| 89|Inf | 4.4773368| 2.627081139|-0.24846136|
## +--------------+---+---+----+----------+------------+-----------+
## |leaning_wall |No |500|Inf | 2.2657445|-0.112117298|-2.11133491|
## | |Yes| 29|Inf | Inf| 3.332204510|-0.06899287|
## +--------------+---+---+----+----------+------------+-----------+
## |tree |No |202|Inf | 1.5976035|-0.678332095|-2.00372972|
## | |Yes|327|Inf | 3.1844436| 0.402917336|-1.86125726|
## +--------------+---+---+----+----------+------------+-----------+
## |downward_floor|No |461|Inf | 2.1757184|-0.292745374|-2.30020130|
## | |Yes| 68|Inf | Inf| 4.204692619|-0.47957308|
## +--------------+---+---+----+----------+------------+-----------+
## |tilted |No |427|Inf | 2.0900237|-0.442687819|-2.51314986|
## | |Yes|102|Inf | Inf| 2.965273066|-0.60613580|
## +--------------+---+---+----+----------+------------+-----------+
## |ground_veg |No |154|Inf | 1.2992830|-1.378197151|-2.77950917|
## | |Yes|375|Inf | 3.2498206| 0.495211396|-1.67820477|
## +--------------+---+---+----+----------+------------+-----------+
## |scars |No |325|Inf | 1.7774735|-1.348266966|-4.38514676|
## | |Yes|204|Inf | Inf| 3.337293580|-0.78275934|
## +--------------+---+---+----+----------+------------+-----------+
## |conc_rainfall |No | 18|Inf |-0.2231436|-2.833213344| -Inf|
## | |Yes|511|Inf | 2.5502894| 0.058725286|-1.87406206|
## +--------------+---+---+----+----------+------------+-----------+
## |wastewater |No |200|Inf | 1.6582281|-0.468378934|-2.75153531|
## | |Yes|329|Inf | 3.0413428| 0.275281559|-1.58412010|
## +--------------+---+---+----+----------+------------+-----------+
## |banana |No |354|Inf | 1.9266788|-0.412532275|-2.14798386|
## | |Yes|175|Inf | 4.4601444| 0.860940637|-1.53582610|
## +--------------+---+---+----+----------+------------+-----------+
## |drainage |Y | 63|Inf | 0.8397507|-1.927891644| -Inf|
## | |P |242|Inf | 2.3536403|-0.541801552|-2.58288706|
## | |N |224|Inf | 3.4339872| 1.074942545|-1.22146596|
## +--------------+---+---+----+----------+------------+-----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.91389034|
## +--------------+---+---+----+----------+------------+-----------+plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
Equation 5 - Based on Equation 1
- based on Eq 1
- less p-value > 0.10 (
# x=TRUE, y=TRUE used by resid() below
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")
eq_OLR_05 <- polr(risk ~ brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_05))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable## Value Std. Error t value p value
## brickTRUE -0.4663079 0.4333423 -1.0760731 1.409473e-01
## woodTRUE 0.9850586 0.3324115 2.9633711 1.521448e-03
## TC_mature_soilTRUE 0.6897894 0.2183751 3.1587360 7.922747e-04
## T_constructionTRUE 0.3517280 0.2277103 1.5446293 6.121798e-02
## crackTRUE 1.8780415 0.3156374 5.9499966 1.340740e-09
## leaning_wallTRUE 1.4451512 0.5244969 2.7553091 2.931836e-03
## scarsTRUE 3.7587610 0.3601930 10.4354095 8.543773e-26
## downward_floorTRUE 1.2206262 0.3424535 3.5643557 1.823755e-04
## tiltedTRUE 1.2102256 0.3047335 3.9714235 3.572223e-05
## conc_rainfallTRUE 1.5644230 0.5282199 2.9616890 1.529783e-03
## wastewaterTRUE 0.7026601 0.2252087 3.1200400 9.041323e-04
## ground_vegTRUE 1.1032074 0.2433719 4.5330108 2.907441e-06
## R1|R2 0.6278189 0.6729307 0.9329622 1.754197e-01
## R2|R3 4.7586091 0.7320817 6.5001066 4.013157e-11
## R3|R4 9.8146315 0.8511334 11.5312492 4.590097e-31stargazer((ctable), type="text", style="default", digits = 2)##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE -0.47 0.43 -1.08 0.14
## woodTRUE 0.99 0.33 2.96 0.002
## TC_mature_soilTRUE 0.69 0.22 3.16 0.001
## T_constructionTRUE 0.35 0.23 1.54 0.06
## crackTRUE 1.88 0.32 5.95 0
## leaning_wallTRUE 1.45 0.52 2.76 0.003
## scarsTRUE 3.76 0.36 10.44 0
## downward_floorTRUE 1.22 0.34 3.56 0.0002
## tiltedTRUE 1.21 0.30 3.97 0.0000
## conc_rainfallTRUE 1.56 0.53 2.96 0.002
## wastewaterTRUE 0.70 0.23 3.12 0.001
## ground_vegTRUE 1.10 0.24 4.53 0.0000
## R1| R2 0.63 0.67 0.93 0.18
## R2| R3 4.76 0.73 6.50 0
## R3| R4 9.81 0.85 11.53 0
## ---------------------------------------------------par(mfrow=c(3,4))
plot.xmean.ordinaly (risk ~ brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ TC_mature_soil+ T_construction+ crack+ leaning_wall+ scars+ downward_floor+ tilted+ conc_rainfall+ wastewater+ ground_veg
, fun=sf))
s## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+-----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+-----------+
## |brick |No | 37|Inf | 2.8622009| 1.287854288|-0.86020127|
## | |Yes|492|Inf | 2.2958961|-0.089490571|-2.03229476|
## +--------------+---+---+----+----------+------------+-----------+
## |wood |No |455|Inf | 2.2344036|-0.171850257|-2.25982323|
## | |Yes| 74|Inf | 3.1640676| 1.134979933|-0.67294447|
## +--------------+---+---+----+----------+------------+-----------+
## |TC_mature_soil|No |252|Inf | 1.8245493|-0.287682072|-2.25129180|
## | |Yes|277|Inf | 3.0948232| 0.254065462|-1.66684882|
## +--------------+---+---+----+----------+------------+-----------+
## |T_construction|No |207|Inf | 1.5581446|-0.896088025|-2.98061864|
## | |Yes|322|Inf | 3.3418976| 0.547435369|-1.51550609|
## +--------------+---+---+----+----------+------------+-----------+
## |crack |No |440|Inf | 2.1477095|-0.358331030|-2.65129738|
## | |Yes| 89|Inf | 4.4773368| 2.627081139|-0.24846136|
## +--------------+---+---+----+----------+------------+-----------+
## |leaning_wall |No |500|Inf | 2.2657445|-0.112117298|-2.11133491|
## | |Yes| 29|Inf | Inf| 3.332204510|-0.06899287|
## +--------------+---+---+----+----------+------------+-----------+
## |scars |No |325|Inf | 1.7774735|-1.348266966|-4.38514676|
## | |Yes|204|Inf | Inf| 3.337293580|-0.78275934|
## +--------------+---+---+----+----------+------------+-----------+
## |downward_floor|No |461|Inf | 2.1757184|-0.292745374|-2.30020130|
## | |Yes| 68|Inf | Inf| 4.204692619|-0.47957308|
## +--------------+---+---+----+----------+------------+-----------+
## |tilted |No |427|Inf | 2.0900237|-0.442687819|-2.51314986|
## | |Yes|102|Inf | Inf| 2.965273066|-0.60613580|
## +--------------+---+---+----+----------+------------+-----------+
## |conc_rainfall |No | 18|Inf |-0.2231436|-2.833213344| -Inf|
## | |Yes|511|Inf | 2.5502894| 0.058725286|-1.87406206|
## +--------------+---+---+----+----------+------------+-----------+
## |wastewater |No |200|Inf | 1.6582281|-0.468378934|-2.75153531|
## | |Yes|329|Inf | 3.0413428| 0.275281559|-1.58412010|
## +--------------+---+---+----+----------+------------+-----------+
## |ground_veg |No |154|Inf | 1.2992830|-1.378197151|-2.77950917|
## | |Yes|375|Inf | 3.2498206| 0.495211396|-1.67820477|
## +--------------+---+---+----+----------+------------+-----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.91389034|
## +--------------+---+---+----+----------+------------+-----------+plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
OLR Equation 6
# x=TRUE, y=TRUE used by resid() below
#print (f1 , latex =TRUE , coefs =5)
#stargazer(anova(f1), type="text", style="default")
eq_OLR_06 <- polr(risk ~ brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana, data= train.data
, method = "logistic", Hess = TRUE)
ctable <- coef(summary(eq_OLR_06))
p<- pnorm(abs(ctable[, "t value"]), lower.tail = FALSE*2) #computes p value
ctable <- cbind(ctable, "p value" = p )
ctable## Value Std. Error t value p value
## brickTRUE -0.83120598 0.5027061 -1.6534632 4.911831e-02
## woodTRUE 0.67020425 0.3356198 1.9969151 2.291720e-02
## mixedTRUE 0.07836333 0.4876315 0.1607019 4.361641e-01
## ENTRUE 0.79586319 0.3841495 2.0717537 1.914421e-02
## TCTRUE -0.20305150 0.4840658 -0.4194708 3.374360e-01
## T_constructionTRUE 0.41457210 0.3568609 1.1617191 1.226748e-01
## landfillTRUE 0.10079726 0.3176051 0.3173666 3.754827e-01
## leakTRUE 0.03402706 0.2241660 0.1517940 4.396747e-01
## garbageTRUE -0.15745163 0.2902313 -0.5425040 2.937357e-01
## crackTRUE 1.80766442 0.3218568 5.6163624 9.750971e-09
## leaning_wallTRUE 1.59519693 0.5426455 2.9396666 1.642828e-03
## treeTRUE -0.03760797 0.2379203 -0.1580696 4.372010e-01
## tiltedTRUE 1.19939706 0.3025243 3.9646305 3.675486e-05
## angleD 0.91536705 0.4529054 2.0211000 2.163470e-02
## angleE 1.32016273 0.5256055 2.5116991 6.007575e-03
## ground_vegTRUE 0.91560884 0.2668482 3.4311979 3.004610e-04
## scarsTRUE 3.80782628 0.3622567 10.5114022 3.827343e-26
## conc_rainfallTRUE 1.86737874 0.5363913 3.4813741 2.494241e-04
## wastewaterTRUE 0.68747410 0.2310714 2.9751591 1.464183e-03
## bananaTRUE 0.61047150 0.2469771 2.4717733 6.722236e-03
## R1|R2 1.36769846 1.0595163 1.2908707 9.837426e-02
## R2|R3 5.46340185 1.0971120 4.9798034 3.182445e-07
## R3|R4 10.47691152 1.2002344 8.7290543 1.284055e-18stargazer((ctable), type="text", style="default", digits = 2)##
## ===================================================
## Value Std. Error t value p value
## ---------------------------------------------------
## brickTRUE -0.83 0.50 -1.65 0.05
## woodTRUE 0.67 0.34 2.00 0.02
## mixedTRUE 0.08 0.49 0.16 0.44
## ENTRUE 0.80 0.38 2.07 0.02
## TCTRUE -0.20 0.48 -0.42 0.34
## T_constructionTRUE 0.41 0.36 1.16 0.12
## landfillTRUE 0.10 0.32 0.32 0.38
## leakTRUE 0.03 0.22 0.15 0.44
## garbageTRUE -0.16 0.29 -0.54 0.29
## crackTRUE 1.81 0.32 5.62 0
## leaning_wallTRUE 1.60 0.54 2.94 0.002
## treeTRUE -0.04 0.24 -0.16 0.44
## tiltedTRUE 1.20 0.30 3.96 0.0000
## angleD 0.92 0.45 2.02 0.02
## angleE 1.32 0.53 2.51 0.01
## ground_vegTRUE 0.92 0.27 3.43 0.0003
## scarsTRUE 3.81 0.36 10.51 0
## conc_rainfallTRUE 1.87 0.54 3.48 0.0002
## wastewaterTRUE 0.69 0.23 2.98 0.001
## bananaTRUE 0.61 0.25 2.47 0.01
## R1| R2 1.37 1.06 1.29 0.10
## R2| R3 5.46 1.10 4.98 0.0000
## R3| R4 10.48 1.20 8.73 0
## ---------------------------------------------------par(mfrow=c(5,4))
plot.xmean.ordinaly (risk ~ brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
,data=train.data, cr=TRUE , subn=FALSE , cex.points =0.65)
sf <- function (y) {
c('y>=1' = qlogis(mean(y>=1)),
'y>=2' = qlogis(mean(y>=2)),
'y>=3' = qlogis(mean(y>=3)),
'y>=4' = qlogis(mean(y>=4)))
}
s<-with(train.data, summary(as.numeric(risk)~brick+ wood+ mixed+ EN+ TC+ T_construction+ landfill+ leak+ garbage+ crack+ leaning_wall+ tree+ tilted+ angle+ ground_veg+ scars+ conc_rainfall+ wastewater+ banana
, fun=sf))
s## as.numeric(risk) N= 529 , 1 Missing
##
## +--------------+---+---+----+----------+------------+-----------+
## | | |N |y>=1|y>=2 |y>=3 |y>=4 |
## +--------------+---+---+----+----------+------------+-----------+
## |brick |No | 37|Inf | 2.8622009| 1.287854288|-0.86020127|
## | |Yes|492|Inf | 2.2958961|-0.089490571|-2.03229476|
## +--------------+---+---+----+----------+------------+-----------+
## |wood |No |455|Inf | 2.2344036|-0.171850257|-2.25982323|
## | |Yes| 74|Inf | 3.1640676| 1.134979933|-0.67294447|
## +--------------+---+---+----+----------+------------+-----------+
## |mixed |No |488|Inf | 2.2869073|-0.098440073|-2.04307390|
## | |Yes| 41|Inf | 2.9704145| 1.268511325|-0.88238918|
## +--------------+---+---+----+----------+------------+-----------+
## |EN |No |343|Inf | 1.8402119|-0.518607764|-2.38209716|
## | |Yes|186|Inf | Inf| 1.000631880|-1.32687094|
## +--------------+---+---+----+----------+------------+-----------+
## |TC |No | 28|Inf | Inf| 1.299282984|-1.29928298|
## | |Yes|501|Inf | 2.2679496|-0.067890336|-1.95736503|
## +--------------+---+---+----+----------+------------+-----------+
## |T_construction|No |207|Inf | 1.5581446|-0.896088025|-2.98061864|
## | |Yes|322|Inf | 3.3418976| 0.547435369|-1.51550609|
## +--------------+---+---+----+----------+------------+-----------+
## |landfill |No |328|Inf | 1.8387844|-0.523855124|-2.53897387|
## | |Yes|201|Inf | 4.6001576| 0.878289614|-1.27205617|
## +--------------+---+---+----+----------+------------+-----------+
## |leak |No |335|Inf | 1.9425030|-0.331357136|-2.43426292|
## | |Yes|194|Inf | 3.6323091| 0.571786324|-1.31686585|
## +--------------+---+---+----+----------+------------+-----------+
## |garbage |No |348|Inf | 2.1288750|-0.207639365|-2.22303246|
## | |Yes|181|Inf | 2.8390785| 0.391671786|-1.46407206|
## +--------------+---+---+----+----------+------------+-----------+
## |crack |No |440|Inf | 2.1477095|-0.358331030|-2.65129738|
## | |Yes| 89|Inf | 4.4773368| 2.627081139|-0.24846136|
## +--------------+---+---+----+----------+------------+-----------+
## |leaning_wall |No |500|Inf | 2.2657445|-0.112117298|-2.11133491|
## | |Yes| 29|Inf | Inf| 3.332204510|-0.06899287|
## +--------------+---+---+----+----------+------------+-----------+
## |tree |No |202|Inf | 1.5976035|-0.678332095|-2.00372972|
## | |Yes|327|Inf | 3.1844436| 0.402917336|-1.86125726|
## +--------------+---+---+----+----------+------------+-----------+
## |tilted |No |427|Inf | 2.0900237|-0.442687819|-2.51314986|
## | |Yes|102|Inf | Inf| 2.965273066|-0.60613580|
## +--------------+---+---+----+----------+------------+-----------+
## |angle |C | 35|Inf | Inf|-0.405465108|-3.52636052|
## | |D |128|Inf | 4.1431347| 1.140723774|-1.22782402|
## | |E |366|Inf | 1.9647786|-0.330854244|-2.15542745|
## +--------------+---+---+----+----------+------------+-----------+
## |ground_veg |No |154|Inf | 1.2992830|-1.378197151|-2.77950917|
## | |Yes|375|Inf | 3.2498206| 0.495211396|-1.67820477|
## +--------------+---+---+----+----------+------------+-----------+
## |scars |No |325|Inf | 1.7774735|-1.348266966|-4.38514676|
## | |Yes|204|Inf | Inf| 3.337293580|-0.78275934|
## +--------------+---+---+----+----------+------------+-----------+
## |conc_rainfall |No | 18|Inf |-0.2231436|-2.833213344| -Inf|
## | |Yes|511|Inf | 2.5502894| 0.058725286|-1.87406206|
## +--------------+---+---+----+----------+------------+-----------+
## |wastewater |No |200|Inf | 1.6582281|-0.468378934|-2.75153531|
## | |Yes|329|Inf | 3.0413428| 0.275281559|-1.58412010|
## +--------------+---+---+----+----------+------------+-----------+
## |banana |No |354|Inf | 1.9266788|-0.412532275|-2.14798386|
## | |Yes|175|Inf | 4.4601444| 0.860940637|-1.53582610|
## +--------------+---+---+----+----------+------------+-----------+
## |Overall | |529|Inf | 2.3277965|-0.003780723|-1.91389034|
## +--------------+---+---+----+----------+------------+-----------+plot(s, which=1:4, pch=1:4, xlab='logit', main=' ', xlim=c(-5,5), cex.lab=0.7, cex.axis=0.5, cex.sub=0.5)
Predicion on test data Eq 1: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html
predictedLevel1 <- predict(eq_OLR_01, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_01, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel1)## predictedLevel1
## R1 R2 R3 R4
## R1 3 14 2 0
## R2 3 82 8 0
## R3 0 13 66 5
## R4 0 0 13 15p1 <- mean(as.character(test.data$risk) != as.character(predictedLevel1)) #misclassification error
p1 ## [1] 0.2589286Predicion on test data Eq 2: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html
predictedLevel2 <- predict(eq_OLR_02, test.data) # predict the levels directly
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel2)## predictedLevel2
## R1 R2 R3 R4
## R1 6 11 2 0
## R2 3 81 9 0
## R3 0 10 67 7
## R4 0 0 14 14p2 <- mean(as.character(test.data$risk) != as.character(predictedLevel2))
p2## [1] 0.25Predicion on test data Eq 3: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html
predictedLevel3 <- predict(eq_OLR_03, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_03, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel3)## predictedLevel3
## R1 R2 R3 R4
## R1 6 11 2 0
## R2 4 82 7 0
## R3 0 12 66 6
## R4 0 0 13 15p3 <- mean(as.character(test.data$risk) != as.character(predictedLevel3))
p3## [1] 0.2455357Predicion on test data Eq 4: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html
predictedLevel4 <- predict(eq_OLR_04, test.data) # predict the levels directly
predictedScores1 <- predict(eq_OLR_04, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel4)## predictedLevel4
## R1 R2 R3 R4
## R1 6 11 2 0
## R2 4 81 8 0
## R3 0 12 66 6
## R4 0 0 14 14p4 <- mean(as.character(test.data$risk) != as.character(predictedLevel4))
p4## [1] 0.2544643Predicion on test data Eq 5: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html
predictedLevel5 <- predict(eq_OLR_05, test.data) # predict the levels directly
predictedScores5 <- predict(eq_OLR_05, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel5)## predictedLevel5
## R1 R2 R3 R4
## R1 3 14 2 0
## R2 2 84 7 0
## R3 0 15 65 4
## R4 0 0 14 14p5 <- mean(as.character(test.data$risk) != as.character(predictedLevel5))
p5## [1] 0.2589286Predicion on test data Eq 6: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html
predictedLevel6 <- predict(eq_OLR_06, test.data) # predict the levels directly
predictedScores6 <- predict(eq_OLR_06, test.data, type="p")
# predict the probabilites
## Confusion matrix and misclassification error
table(test.data$risk, predictedLevel6)## predictedLevel6
## R1 R2 R3 R4
## R1 4 13 2 0
## R2 1 84 8 0
## R3 0 17 60 7
## R4 0 0 13 15p6 <- mean(as.character(test.data$risk) != as.character(predictedLevel6))
p6## [1] 0.2723214Predicion on test data Eq 7: http://r-statistics.co/Ordinal-Logistic-Regression-With-R.html
#Table
df2 <- data.frame(
"Equations"=c(1:6),
"Predicted"=c(1-p1,
1-p2,
1-p3,
1-p4,
1-p5,
1-p6
)
)
df2## Equations Predicted
## 1 1 0.7410714
## 2 2 0.7500000
## 3 3 0.7544643
## 4 4 0.7455357
## 5 5 0.7410714
## 6 6 0.7276786